The association between visceral adiposity index and risk of type 2 diabetes mellitus

Relationships between the visceral adiposity index (VAI) and type 2 diabetes mellitus (T2DM) have been underexplored. The purpose of this study is to explore association between VAI and T2DM in adults in the US. Based on the National Health and Nutrition Examination Survey 2007–2018, 11,214 participants aged 20 years or older were included in a cross-sectional study. Multifactorial logistic regression analysis and smoothed curve fitting analysis were performed to investigate links between VAI and the prevalence of T2DM, as well as the stability and incidence between subgroups. In a fully adjusted continuous model, the aggregate population risk of T2DM increased 0.43-fold with each 1-unit increase in VAI [odds ratio (OR) = 1.43; 95% confidence interval (CI) 1.35–1.50]. In the fully adjusted categorical model with VAI scores stratified by quartiles, results showed a higher T2DM advantage among participants in the second, third, and fourth quartiles (Q2: OR 1.35, 95% CI 1.06–1.71; Q3: OR 2.46, 95% CI 1.95–3.11; Q4: OR 4.42, 95% CI 3.55–05.50). Compared with Q1, the prevalence of T2DM in the total population increased 3.42-fold in Q4. The above results indicated that VAI was positively associated with the prevalence of T2DM, which was consistent and nonlinear with the smoothed curve-fitting analysis (P for non-linear = 0). Subgroup analyses after adjusting for covariates showed that keeping with the overall population results, it also was found that there was an interaction between sex and hypertension in the subgroups. VAI was positively associated with the prevalence of T2DM and was more prevalent in women, non-hypertensive than in men, hypertensive populations.


Data collection
Information was extracted and recorded by specialized personnel.The information extracted included age, gender, ethnics, education, marriage status, Income to poverty ratio (PIR), BMI, WC, smoking status, and alcohol consumption, estimated glomerular filtration rate (eGFR), physical activity, as well as data regarding typical biochemical markers, such as blood TG levels.The information also included self-reported answers to questionnaires related to hypertension, coronary heart disease, stroke, and heart failure.As part of the original survey, relevant personnel collated the basic information, and the biochemical samples were stored appropriately prior to submission to laboratories of the University of Minnesota and the University of Missouri-Columbia for examination and analysis.

Selection of covariates
The main covariates considered included the demographic factors age; sex (male or female); race (Mexican-American, non-Hispanic white, non-Hispanic black, other Hispanic, and other races); educational attainment (less than 9th grade, 9th-11th grade, high school diploma, some college, or completion of college and above); and marriage status (married, widowed, divorced, separated, unmarried, or cohabitating); PIR (< 1.3, 1.3-3.5, ≥ 3.5).They also included the health-related behaviors smoking (former, current, or never) and alcohol consumption (former, light, heavy, or non-drinking), physical activity.The laboratory markers included: total cholesterol (TC), low-density lipoproteins (LDL), fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), alanine aminotransferase (ALT), and aspartate aminotransferase (AST).Common underlying diseases were also included.These diseases included hypertension, which was recognized as satisfying any one of these criteria: self-reported physician diagnosis of hypertension; current usage of BP-lowering drugs, or average of 3 measurements of blood pressure with systolic blood pressure (SBP) ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg.They also included coronary heart disease (CHD), stroke, and heart failure; each of these diseases was monitored according to self-reporting of a physician's diagnosis.Specific technical methods regarding covariate determination are available from the official NHANES website.

Statistical analysis
The survey data were analyzed using R (version 4.3.1).Continuous variables are expressed as mean ± standard deviation, and categorical variables are expressed as frequencies (percentages).Differences between categorical variables were analyzed using the chi-square test, and differences between continuous variables were assessed using the weighted Student's t-test test or the Mann-Whitney U-test, depending on the nature of the distribution.The level of statistical significance was set at P < 0.05.The association between VAI and T2DM in adults from the US was analyzed by building three multivariate logistic regression models.Model 1 was not adjusted for confounders; model 2 was adjusted for age, gender, and ethnicity; model 3 was further adjusted for education, marriage status, PIR, smoking, and alcohol consumption, physical activity, eGFR, AST, AST, TC, LDL, hypertension, coronary heart disease, stroke, and heart failure.Smoothed curve fitting was then used to explore whether there was a non-linear relationship between VAI and T2DM.Finally, the confounders listed in the baseline table age (20-34, 35-54, 55-74, ≥ 75), sex (male or female), race (Mexican-American, non-Hispanic white, non-Hispanic black, other Hispanic, and other races), smoking, alcohol consumption, eGFR (< 90, ≥ 90), CHD (yes/no), stroke (yes/no), and heart failure (yes/no) were analyzed using stratified logistic regression modeling in a subgroup analysis for the presence of interactions.
The studies involving human participants were reviewed and approved by The Research Ethics Review Board at the National Center for Health Statistics (NCHS).The patients/participants provided their written informed consent to participate in this study.

Baseline characteristics
The final inclusion of 11,214 patients in this study is shown in Fig. 1.The baseline characteristics by different disease states are shown in Table 1.The weighted mean age of the participants was 47.65 ± 0.29 years.Among the study participants, 49.00% were male, and 51.00% were female.VAI values were higher in diabetic patients than in non-diabetic patients.Supplementary Table S1, the participants were divided into four groups based on VAI quartiles; the values of VAI in these quartiles (as mean ± SD) were Q1, 0.59 ± 0.00; Q2, 1.10 ± 0.00; Q3, 1.79 ± 0.01; and Q4, 3.74 ± 0.04.Compared with subjects in Q1, subjects in Q4 were higher in age and more likely to be female and to belong to the non-Hispanic white demographic.As compared with subjects in Q1, subjects in Q4 had a higher average level of education, were more likely to be married, were more likely to be non-smokers and to not consume alcohol.In addition, subjects in Q4 had higher levels of BMI, WC, PIR, FDG, HbA1c, TC, TG, LDL, ALT, and AST, and higher levels of hypertension, coronary heart disease, stroke, and heart failure.As compared

Association between VAI and T2DM
Logistic regression models were used to analyze the association among VAI and the prevalence of T2DM as shown in Table 2.In fully adjusted continuous models, the prevalence of T2DM in the total population increased 0. ).The prevalence of T2DM in the total population increased 3.42-fold in Q4 compared to Q1.A trend test was performed to ensure the stability of the results of this study, and the incidence of VAI and T2DM showed a monotonically increasing trend in all models (P < 0.0001).In summary, it can be seen that VAI was positively correlated with the incidence of T2DM.We plotted a smoothed curve fit as shown in Fig. 2, and

Subgroup analysis
Subgroup analyses, as shown in Fig. 3, showed that the prevalence between VAI and T2DM remained stable across age, race, eGFR, smoking, alcohol consumption, angina, stroke, and heart failure, and there was no interaction.We found a significant interaction in the subgroup of sex (male/female) (P < 0.001).In women, for every 1-unit increase in VAI, there was a 0.50-fold increase in the incidence of T2DM (OR 1.50, 95% CI 1.39-1.63).
For men, each 1-unit increase in VAI was linked to a 0.32-fold increase in the odds of developing T2DM (OR 1.32, 95% CI 1. 25-1.40).We also found an interaction in the subgroup of hypertensive (yes/no) (P = 0.03).In the hypertensive population, each 1-unit increase in VAI was accompanied by a 0.36-fold increase in the prevalence of T2DM (OR 1.36, 95% CI 1.28-1.45),whereas in the non-hypertensive population, each 1-unit increase in VAI was accompanied by a 0.51-fold increase in the prevalence of T2DM (OR 1.51, 95% CI 1.40-1.65).As shown in Fig. 4, women were more likely to develop T2DM than men (Fig. 4A) and as VAI increased nonhypertensive patients were more likely to develop T2DM than hypertensive patients (Fig. 4B).

Discussion
In this research study that investigated the association between VAI and T2DM in adults in the US using a large 6-period cross-sectional study from the NHANES database, the main finding that VAI is positively associated with T2DM, while the non-linear association between VAI and T2DM is a secondary result.Thus, we propose that VAI can be used as a predictor of T2DM.A total of 11,214 subjects were included, and the prevalence of T2DM was 15.83%.After adjusting for confounders, each 1-unit increase of VAI was related to a 43% rise in T2DM prevalence.When VAI was considered as a categorical variable, the prevalence of T2DM was significantly higher in VAI quartile four than in quartile one.Our subgroup analysis uncovered an interaction between gender and hypertension in both subgroups and a higher prevalence in the female, non-hypertensive population than in the male, hypertensive population.The higher prevalence in women than in men is due to the role of estrogen in regulating insulin sensitivity.Estrogen acts as a protector of ectopic lipids by inhibiting the inflammatory response in white fat, which in turn inhibits oxidative stress 19,20 .With aging women have less estrogen and are more prone to IR than men.Koutsari found that women have a higher capacity to process non-oxidized free fatty acids (FFA) than men, and that non-oxidized processing of free fatty acids may increase very low-density lipoproteins (VLDL) and TG and cause insulin resistance (IR), leading to metabolic disorders 21 .In addition, it has been shown that fatty acid oxidation rates differ between genders, with women having lower levels of basal fatty acid oxidation and being more susceptible to metabolic disorders 22 .Therefore, in the future, we should pay more attention to T2DM in female, non-hypertensive population and explore it through basic experiments.
As quality of life improves and diet structures are altered, the prevalence of obesity is growing worldwide 23 .Persons with higher fat accumulation and obesity are more likely to suffer from T2DM, hypertension, and atherosclerosis, and these issues have measurable effects on the human life span 24,25 .Persons with fat concentrated near visceral organs are more susceptible to insulin resistance and T2DM than are persons in which fat deposition tends to be more subcutaneous 26,27 .Although BMI is the most frequently used method for assessing total fat deposition, it cannot differentiate between subcutaneous and visceral fat and thus cannot accurately evaluate obesity 28 .Similarly, WC, a simple and reliable measure for assessing abdominal obesity, has been used to measure total body fat 29 , but this measure, like BMI, cannot differentiate between subcutaneous and visceral fat 30 .Compared with BMI and WC, VAI can evaluate visceral fat distribution effectively and has good predictive ability, and this measure has been shown to be closely related to metabolic diseases 31,32 .VAI is a relatively simple and rapid assessment that is less costly than other tools, and it is on the cutting edge of glucose and insulin.An additional strength of VAI is that it includes both anthropometric parameters and metabolic indexes, which are useful in the evaluation of the distribution of visceral fat and functional abnormalities 33 .The VAI index has been reported to be significantly associated with metabolic syndromes including insulin resistance 34,35 , and the use of VAI has played an important role in the evaluation of hypertension, abdominal aortic calcification, and cardiovascular diseases 14,36,37 .
Diabetes mellitus is a multifactorial metabolic disease with a complex etiology involving genetic, environmental, physiological, behavioral, social, and economic factors 38 , and T2DM is the primary manifestation of this disorder.Obesity is often associated with abnormalities of lipid metabolism, and the more accumulated fat correlates with a higher the risk of T2DM in both male and female subjects.Increased adipose tissue leads to insulin resistance, reduced systemic inflammatory responses, and immune-metabolic disorders, resulting in decreased β-cell function and abnormally elevated blood glucose 39 .In T2DM, as adipocytes continue to increase, adipose tissue expands abnormally, leading to increased surface area, which lowers glucose transport efficiency and reduces the cellular insulin response, leading to diabetes 40 .Multiple studies have shown the utility of VAI in the clinical assessment of metabolic disorders.A cross-sectional study by Kai et al. 35 included 27,309 adults in the United States and found that higher VAI was associated with insulin resistance(IR), and the VAI value could be used as a predictor of risk of developing IR.In another study that also included 4437 participants, Yuan et al. 7 found that VAI was an independent risk indicator for FPG with good predictive value and could be used as a surrogate for clinical assessment of risk of hyperglycemia and could be used to guide treatment of hyperglycemia.Han et al. 41 concluded that VAI was positively correlated with the risk of T2DM in a rural study in China.Shang et al. 42 explored the association between VAI and the risk of T2DM in Japanese adults.Kalapur et al. 43 found that VAI was higher in 30 DM patients than in 30 non-DM patients and thus that there was a correlation between  44 included 824 first-degree relatives of T2DM patients with an unknown history of abnormal glucose regulation, and the subjects had higher average VAI values than did those with normal glucose regulation.These studies and our own work have consistently shown that VAI is closely related to T2DM, and thus we believe that a large-sample cross-sectional study is warranted.The present study was associated with several limitations.First, as the study was a cross-sectional analysis, a causal relationship between VAI and T2DM prevalence could not be determined.Second, although adjustments for confounders were made, bias due to unknown factors could not be wholly excluded.In addition, the survey

Figure 3 .
Figure 3. Subgroup analysis for the association between VAI and T2DM.
with subjects in Q1, subjects in Q4 were less likely to belong to the physical activity, and they had lower levels of eGFR and HDL.Differences in age, race, education, marriage, PIR, smoking, alcohol consumption, BMI, WC, FDG, HbA1c, TC, TG, LDL, HDL, eGFR, AST, AST, physical activity, hypertension, coronary artery disease and heart failure were statistically significant among all four quartiles (P < 0.05).

Table 2 .
The after adjusting for confounders such as age, sex, race, education, marriage, PIR, smoking, alcohol consumption, physical activity, eGFR, AST, AST, TC, LDL, hypertension, coronary heart disease, stroke, and heart failure, we found that VAI and T2DM prevalence were consistent and nonlinearly associated with multifactorial logistic regression (P for non-near = 0 < 0.05).